Pub Date : 2022-11-10DOI: 10.1108/ijlss-10-2021-0171
K. Srinivasan, V. Yadav, Anish Kumar, Balaganesh Margabandu, Janish Selvaraj, Anshu Kumar
Purpose This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work. Design/methodology/approach Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS). Findings From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers. Practical implications This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic. Originality/value The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.
{"title":"Prioritizing the mitigation strategies to lean and green barriers using fuzzy BWM-FTOPSIS method in the food supply chain: an empirical case study","authors":"K. Srinivasan, V. Yadav, Anish Kumar, Balaganesh Margabandu, Janish Selvaraj, Anshu Kumar","doi":"10.1108/ijlss-10-2021-0171","DOIUrl":"https://doi.org/10.1108/ijlss-10-2021-0171","url":null,"abstract":"\u0000Purpose\u0000This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work.\u0000\u0000\u0000Design/methodology/approach\u0000Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS).\u0000\u0000\u0000Findings\u0000From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers.\u0000\u0000\u0000Practical implications\u0000This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic.\u0000\u0000\u0000Originality/value\u0000The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44570662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-09DOI: 10.1108/ijlss-02-2022-0046
Meryem Uluskan, Merve Gizem Karşı
Purpose This study aims to emphasize utilization of Predictive Six Sigma to achieve process improvements based on machine learning (ML) techniques embedded in define, measure, analyze, improve, control (DMAIC). With this aim, this study presents selection and utilization of ML techniques, including multiple linear regression (MLR), artificial neural network (ANN), random forests (RF), gradient boosting machines (GBM) and k-nearest neighbors (k-NN) in the analyze and improve phases of Six Sigma DMAIC. Design/methodology/approach A data set containing 320 observations with nine input and one output variables is used. To achieve the objective which was to decrease the number of fabric defects, five ML techniques were compared in terms of prediction performance and best tools were selected. Next, most important causes of defects were determined via these tools. Finally, parameter optimization was conducted for minimum number of defects. Findings Among five ML tools, ANN, GBM and RF are found to be the best predictors. Out of nine potential causes, “machine speed” and “fabric width” are determined as the most important variables by using these tools. Then, optimum values for “machine speed” and “fabric width” for fabric defect minimization are determined both via regression response optimizer and ANN surface optimization. Ultimately, average defect number was decreased from 13/roll to 3/roll, which is a considerable decrease attained through utilization of ML techniques in Six Sigma. Originality/value Addressing an important gap in Six Sigma literature, in this study, certain ML techniques (i.e. MLR, ANN, RF, GBM and k-NN) are compared and the ones possessing best performances are used in the analyze and improve phases of Six Sigma DMAIC.
{"title":"Predictive Six Sigma for Turkish manufacturers: utilization of machine learning tools in DMAIC","authors":"Meryem Uluskan, Merve Gizem Karşı","doi":"10.1108/ijlss-02-2022-0046","DOIUrl":"https://doi.org/10.1108/ijlss-02-2022-0046","url":null,"abstract":"\u0000Purpose\u0000This study aims to emphasize utilization of Predictive Six Sigma to achieve process improvements based on machine learning (ML) techniques embedded in define, measure, analyze, improve, control (DMAIC). With this aim, this study presents selection and utilization of ML techniques, including multiple linear regression (MLR), artificial neural network (ANN), random forests (RF), gradient boosting machines (GBM) and k-nearest neighbors (k-NN) in the analyze and improve phases of Six Sigma DMAIC.\u0000\u0000\u0000Design/methodology/approach\u0000A data set containing 320 observations with nine input and one output variables is used. To achieve the objective which was to decrease the number of fabric defects, five ML techniques were compared in terms of prediction performance and best tools were selected. Next, most important causes of defects were determined via these tools. Finally, parameter optimization was conducted for minimum number of defects.\u0000\u0000\u0000Findings\u0000Among five ML tools, ANN, GBM and RF are found to be the best predictors. Out of nine potential causes, “machine speed” and “fabric width” are determined as the most important variables by using these tools. Then, optimum values for “machine speed” and “fabric width” for fabric defect minimization are determined both via regression response optimizer and ANN surface optimization. Ultimately, average defect number was decreased from 13/roll to 3/roll, which is a considerable decrease attained through utilization of ML techniques in Six Sigma.\u0000\u0000\u0000Originality/value\u0000Addressing an important gap in Six Sigma literature, in this study, certain ML techniques (i.e. MLR, ANN, RF, GBM and k-NN) are compared and the ones possessing best performances are used in the analyze and improve phases of Six Sigma DMAIC.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46409026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-08DOI: 10.1108/ijlss-02-2022-0042
R. Rathi, Mahender Singh Kaswan, J. Antony, Jennifer Cross, J. Garza‐Reyes, S. Furterer
Purpose Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility. Design/methodology/approach Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors. Findings Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress. Research limitations/implications The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development. Originality/value This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.
{"title":"Success factors for the adoption of green lean six sigma in healthcare facility: an ISM-MICMAC study","authors":"R. Rathi, Mahender Singh Kaswan, J. Antony, Jennifer Cross, J. Garza‐Reyes, S. Furterer","doi":"10.1108/ijlss-02-2022-0042","DOIUrl":"https://doi.org/10.1108/ijlss-02-2022-0042","url":null,"abstract":"\u0000Purpose\u0000Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility.\u0000\u0000\u0000Design/methodology/approach\u0000Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors.\u0000\u0000\u0000Findings\u0000Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress.\u0000\u0000\u0000Research limitations/implications\u0000The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development.\u0000\u0000\u0000Originality/value\u0000This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45992152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1108/ijlss-04-2022-0090
R. Hellberg, E. Fauskanger
Purpose The purpose of this study is to investigate how professionals who are continuing their education rate a higher education quality management course with an emphasis on reflective learning and real problem-solving. The audited course consists of module-based teaching, while students work on an improvement project at their workplace between course sessions. This study has a twofold aim: to contribute to the design of quality improvement courses based on doing as we learn and to offer insight into the use of a final grading method that consist of a folder with reports from the intermediate work steps and a final report. Design/methodology/approach After completing the course, students received a survey with questions and statements about the course content, delivery and final grading methods. They answered these questions on a seven-point Likert scale and also answered open-ended questions. Findings It is clear that professional students value the interweaving of theory with real-life training, and they value module-based teaching in which theory is reviewed and applied to practical problems. Reflective learning was achieved through feedback from both teachers and fellow students on various interim reports. Students’ employers benefit from the course, as students gain experience with quality improvement. The grading of a final report on the improvement project based on three sub-assignments was highly appreciated. Practical implications Developers in courses in quality improvement benefit from learning how this course is structured, assessed and how participants perceived its components. Originality/value The course design with modules and intermediate work steps, where the students apply theory in quality improvement to a real project at their workplace, is an original concept. The modules correspond to the plan, do, check and act (PDCA) methodology.
{"title":"Learning of quality improvement theory – experiences with reflective learning from a student perspective","authors":"R. Hellberg, E. Fauskanger","doi":"10.1108/ijlss-04-2022-0090","DOIUrl":"https://doi.org/10.1108/ijlss-04-2022-0090","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is to investigate how professionals who are continuing their education rate a higher education quality management course with an emphasis on reflective learning and real problem-solving. The audited course consists of module-based teaching, while students work on an improvement project at their workplace between course sessions. This study has a twofold aim: to contribute to the design of quality improvement courses based on doing as we learn and to offer insight into the use of a final grading method that consist of a folder with reports from the intermediate work steps and a final report.\u0000\u0000\u0000Design/methodology/approach\u0000After completing the course, students received a survey with questions and statements about the course content, delivery and final grading methods. They answered these questions on a seven-point Likert scale and also answered open-ended questions.\u0000\u0000\u0000Findings\u0000It is clear that professional students value the interweaving of theory with real-life training, and they value module-based teaching in which theory is reviewed and applied to practical problems. Reflective learning was achieved through feedback from both teachers and fellow students on various interim reports. Students’ employers benefit from the course, as students gain experience with quality improvement. The grading of a final report on the improvement project based on three sub-assignments was highly appreciated.\u0000\u0000\u0000Practical implications\u0000Developers in courses in quality improvement benefit from learning how this course is structured, assessed and how participants perceived its components.\u0000\u0000\u0000Originality/value\u0000The course design with modules and intermediate work steps, where the students apply theory in quality improvement to a real project at their workplace, is an original concept. The modules correspond to the plan, do, check and act (PDCA) methodology.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41888075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-12DOI: 10.1108/ijlss-06-2021-0104
Ali Ahmed, J. Olsen, J. Page
Purpose The overarching objective of this research is to integrate the Lean Six Sigma (LSS) framework with computer simulation to improve the production efficiency of a light-emitting diode (LED) manufacturing factory. Design/methodology/approach Recently, the idea of taking advantage of the benefits of Six Sigma and simulation models together has led both industry and the academy towards further investigation and implementation of these methodologies. From this perspective, the present research will illustrate the effectiveness of using LSS methodology in a real factory environment by using the combination of three simulation methods which are system dynamics (SD), discrete-event simulation (DES) and agent-based (AB) modelling. Findings The hybrid simulation method applied in this research was found to accurately mimic and model the existing real factory environment. The define, measure, analyse, control and improve (DMAIC)-based improvements showed that the applied method is able to improve machine utilization rates while balancing the workload. Moreover, queue lengths for several stations were shortened, and the average processing time was decreased by around 50%. Also, a weekly production increase of 25% was achieved while lowering the cost per unit by around 8%. Research limitations/implications While the case study used was for a LED manufacturing system, the proposed framework could be implemented for any other existing production system. The research also meticulously presents the steps carried out for the development of the multi-method simulation model to allow readers to replicate the model and tailor it for their own case studies and projects. The hybrid model enables managers to navigate the trade-off decisions they often face when choosing advanced production output ahead of continuous improvement practices. The adoption of methodologies outlined in this paper would attain improvements in terms of queue lengths, utilization, reduced costs and improved quality and efficiency of a real, small factory. The findings suggest improvements and create awareness among practitioners for the utilization of quality tools that will provide direct benefits to their companies. Although the multi-method simulation is effective, a limitation of the current study is the lack of micro details within each station. Furthermore, the results are all based on one specific case study which is not enough to suggest and generalized findings. Originality/value This research combines the use of the three main hybrid simulation paradigms (SD, DES and AB) in a unified framework DMAIC methodology. Choosing the right models in DMAIC is important, challenging and urgently necessary. Also, this paper shows empirical evidence on its effectiveness.
{"title":"Integration of Six Sigma and simulations in real production factory to improve performance – a case study analysis","authors":"Ali Ahmed, J. Olsen, J. Page","doi":"10.1108/ijlss-06-2021-0104","DOIUrl":"https://doi.org/10.1108/ijlss-06-2021-0104","url":null,"abstract":"\u0000Purpose\u0000The overarching objective of this research is to integrate the Lean Six Sigma (LSS) framework with computer simulation to improve the production efficiency of a light-emitting diode (LED) manufacturing factory.\u0000\u0000\u0000Design/methodology/approach\u0000Recently, the idea of taking advantage of the benefits of Six Sigma and simulation models together has led both industry and the academy towards further investigation and implementation of these methodologies. From this perspective, the present research will illustrate the effectiveness of using LSS methodology in a real factory environment by using the combination of three simulation methods which are system dynamics (SD), discrete-event simulation (DES) and agent-based (AB) modelling.\u0000\u0000\u0000Findings\u0000The hybrid simulation method applied in this research was found to accurately mimic and model the existing real factory environment. The define, measure, analyse, control and improve (DMAIC)-based improvements showed that the applied method is able to improve machine utilization rates while balancing the workload. Moreover, queue lengths for several stations were shortened, and the average processing time was decreased by around 50%. Also, a weekly production increase of 25% was achieved while lowering the cost per unit by around 8%.\u0000\u0000\u0000Research limitations/implications\u0000While the case study used was for a LED manufacturing system, the proposed framework could be implemented for any other existing production system. The research also meticulously presents the steps carried out for the development of the multi-method simulation model to allow readers to replicate the model and tailor it for their own case studies and projects. The hybrid model enables managers to navigate the trade-off decisions they often face when choosing advanced production output ahead of continuous improvement practices. The adoption of methodologies outlined in this paper would attain improvements in terms of queue lengths, utilization, reduced costs and improved quality and efficiency of a real, small factory. The findings suggest improvements and create awareness among practitioners for the utilization of quality tools that will provide direct benefits to their companies. Although the multi-method simulation is effective, a limitation of the current study is the lack of micro details within each station. Furthermore, the results are all based on one specific case study which is not enough to suggest and generalized findings.\u0000\u0000\u0000Originality/value\u0000This research combines the use of the three main hybrid simulation paradigms (SD, DES and AB) in a unified framework DMAIC methodology. Choosing the right models in DMAIC is important, challenging and urgently necessary. Also, this paper shows empirical evidence on its effectiveness.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44507573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.1108/ijlss-06-2022-0135
Dejian Yu, Tong Ye
Purpose The purpose of this paper is to contribute to the existing knowledge system of lean supply chain management (LSCM), i.e. by using main path analysis, and the authors extract the main development track of LSCM. It is advantageous for relevant scholars to deepen their understanding of this academic field from a bibliometrics view to grasp the future directions better. Design/methodology/approach Structuring a citation network with the processed data set containing 866 papers and relevant information collected from Web of Science (WoS). Conducting review analyses aiming at the main paths that are extracted from the above citation network. Findings There are two different evolution paths in LSCM field, i.e. improving corporate sustainability performance through combining lean and green practices, and seeking the balance between lean and agility to structure leagile supply chain for specific industries. LSCM research studies mainly focus on five aspects: (1) establishment and development of LSCM theory; (2) structuration of lean supply chain; (3) research studies of the relationship between LSCM and corporate performance; (4) supply chain evaluation system; and (5) review and vista of LSCM field. The intersection of two knowledge evolute routes would be Industry 4.0, which is an integrated theory system combining lean, agility, green and other supply chain thinking. Research limitations/implications The data set collected from WoS cannot contain all the research studies about LSCM is the main research limitation. Sustainability, as represented by environmental performance, will continue to be a major pursuit of this field. Integrating LSCM in Industry 4.0 will be the next hotspot in LSCM field. Practical implications Providing the main research contents and common methods of LSCM field. It is conducive to deepening the understanding of relevant practitioners and scholars to LSCM field from a dynamic perspective. Originality/value To the best of the authors’ knowledge, it is the first time to reveal the knowledge diffuse trajectories of LSCM under different view with main path analysis. This study is unique that it provides a new view to understand the field of LSCM.
{"title":"Tracing the lean thinking in supply chain management: a comprehensive main path analysis","authors":"Dejian Yu, Tong Ye","doi":"10.1108/ijlss-06-2022-0135","DOIUrl":"https://doi.org/10.1108/ijlss-06-2022-0135","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to contribute to the existing knowledge system of lean supply chain management (LSCM), i.e. by using main path analysis, and the authors extract the main development track of LSCM. It is advantageous for relevant scholars to deepen their understanding of this academic field from a bibliometrics view to grasp the future directions better.\u0000\u0000\u0000Design/methodology/approach\u0000Structuring a citation network with the processed data set containing 866 papers and relevant information collected from Web of Science (WoS). Conducting review analyses aiming at the main paths that are extracted from the above citation network.\u0000\u0000\u0000Findings\u0000There are two different evolution paths in LSCM field, i.e. improving corporate sustainability performance through combining lean and green practices, and seeking the balance between lean and agility to structure leagile supply chain for specific industries. LSCM research studies mainly focus on five aspects: (1) establishment and development of LSCM theory; (2) structuration of lean supply chain; (3) research studies of the relationship between LSCM and corporate performance; (4) supply chain evaluation system; and (5) review and vista of LSCM field. The intersection of two knowledge evolute routes would be Industry 4.0, which is an integrated theory system combining lean, agility, green and other supply chain thinking.\u0000\u0000\u0000Research limitations/implications\u0000The data set collected from WoS cannot contain all the research studies about LSCM is the main research limitation. Sustainability, as represented by environmental performance, will continue to be a major pursuit of this field. Integrating LSCM in Industry 4.0 will be the next hotspot in LSCM field.\u0000\u0000\u0000Practical implications\u0000Providing the main research contents and common methods of LSCM field. It is conducive to deepening the understanding of relevant practitioners and scholars to LSCM field from a dynamic perspective.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, it is the first time to reveal the knowledge diffuse trajectories of LSCM under different view with main path analysis. This study is unique that it provides a new view to understand the field of LSCM.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44266701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-20DOI: 10.1108/ijlss-02-2022-0035
P. Hines, Torbjørn H. Netland
Purpose This paper reports exploratory findings about teaching in the metaverse using a virtual reality (VR) platform and head-mounted displays. This paper addresses three research questions: Is the metaverse an appropriate platform for teaching Lean? What are the benefits and problems of this approach over traditional classroom methods? What are the future implications for teaching Lean in the VR-enabled metaverse? Design/methodology/approach The research presented in this paper is exploratory. A critical realism approach is adopted using action research through the preparation, delivery and review of the first four masterclasses entitled Leading Intelligent Lean offered by Gemba (formerly The Leadership Network). The data collection methods included a pre-workshop questionnaire, participant observation, focus groups and end-of-course surveys. Findings It was found that Lean can be taught successfully in the metaverse. There are many related benefits, particularly in terms of the high levels of immersion and the “wow” factor. Remaining technological limitations are reduced by continually improving the metaverse platform and the course content and delivery. The authors conclude that the metaverse is a useful addition to teaching Lean – and is especially promising when used in a blended teaching approach. Originality/value To the best of the authors’ knowledge, this is the first report of teaching Lean in a VR-enabled metaverse and one of the first of teaching and learning in the metaverse regardless of topic. The respective problems and benefits of this approach versus teaching in a traditional classroom setting are discussed.
{"title":"Teaching a Lean masterclass in the metaverse","authors":"P. Hines, Torbjørn H. Netland","doi":"10.1108/ijlss-02-2022-0035","DOIUrl":"https://doi.org/10.1108/ijlss-02-2022-0035","url":null,"abstract":"\u0000Purpose\u0000This paper reports exploratory findings about teaching in the metaverse using a virtual reality (VR) platform and head-mounted displays. This paper addresses three research questions: Is the metaverse an appropriate platform for teaching Lean? What are the benefits and problems of this approach over traditional classroom methods? What are the future implications for teaching Lean in the VR-enabled metaverse?\u0000\u0000\u0000Design/methodology/approach\u0000The research presented in this paper is exploratory. A critical realism approach is adopted using action research through the preparation, delivery and review of the first four masterclasses entitled Leading Intelligent Lean offered by Gemba (formerly The Leadership Network). The data collection methods included a pre-workshop questionnaire, participant observation, focus groups and end-of-course surveys.\u0000\u0000\u0000Findings\u0000It was found that Lean can be taught successfully in the metaverse. There are many related benefits, particularly in terms of the high levels of immersion and the “wow” factor. Remaining technological limitations are reduced by continually improving the metaverse platform and the course content and delivery. The authors conclude that the metaverse is a useful addition to teaching Lean – and is especially promising when used in a blended teaching approach.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, this is the first report of teaching Lean in a VR-enabled metaverse and one of the first of teaching and learning in the metaverse regardless of topic. The respective problems and benefits of this approach versus teaching in a traditional classroom setting are discussed.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44867895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-08DOI: 10.1108/ijlss-01-2022-0020
Y. Kose, Suleyman Muftuoglu, E. Çevikcan, M. B. Durmusoglu
Purpose Autonomous maintenance (AM), one of the pillars of total productive maintenance (TPM), aims to achieve performance toward zero defects and zero breakdowns. AM system equipped with comprehensive lean tools provides continuous improvement during the AM activities. Despite its long duration, establishing a lean AM system with a robust guideline would provide significant benefits such as high quality and short lead time. Therefore, AM design approach should be provided in a holistic and detailed manner. This study aims to develop a framework for AM design, including preliminary, reactive, preventive and proactive steps using the axiomatic design (AD). Design/methodology/approach Requirements and technical parameters of the AM system are explored with AD. An extensive literature review and a real-life application are presented. Findings The proposed design was validated by adapting the proposed roadmap to a textile manufacturing system in Turkey. The application results justify the established AM system design with an average downtime improvement of 69.2% and the average elapsed time between two failures improvement of 65.1% for apparel department. Originality/value This study has the novelty of establishing an overall AM system design with all of its stages stepwise. It presents a comprehensive guideline in terms of integration of lean philosophy into AM design by generating maintenance-related use cases for lean tools. The developed approach facilitates creating and analyzing complex systems to improve maintenance implementations while reducing nonvalue-added operations.
{"title":"Axiomatic design for lean autonomous maintenance system: an application from textile industry","authors":"Y. Kose, Suleyman Muftuoglu, E. Çevikcan, M. B. Durmusoglu","doi":"10.1108/ijlss-01-2022-0020","DOIUrl":"https://doi.org/10.1108/ijlss-01-2022-0020","url":null,"abstract":"\u0000Purpose\u0000Autonomous maintenance (AM), one of the pillars of total productive maintenance (TPM), aims to achieve performance toward zero defects and zero breakdowns. AM system equipped with comprehensive lean tools provides continuous improvement during the AM activities. Despite its long duration, establishing a lean AM system with a robust guideline would provide significant benefits such as high quality and short lead time. Therefore, AM design approach should be provided in a holistic and detailed manner. This study aims to develop a framework for AM design, including preliminary, reactive, preventive and proactive steps using the axiomatic design (AD).\u0000\u0000\u0000Design/methodology/approach\u0000Requirements and technical parameters of the AM system are explored with AD. An extensive literature review and a real-life application are presented.\u0000\u0000\u0000Findings\u0000The proposed design was validated by adapting the proposed roadmap to a textile manufacturing system in Turkey. The application results justify the established AM system design with an average downtime improvement of 69.2% and the average elapsed time between two failures improvement of 65.1% for apparel department.\u0000\u0000\u0000Originality/value\u0000This study has the novelty of establishing an overall AM system design with all of its stages stepwise. It presents a comprehensive guideline in terms of integration of lean philosophy into AM design by generating maintenance-related use cases for lean tools. The developed approach facilitates creating and analyzing complex systems to improve maintenance implementations while reducing nonvalue-added operations.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46425226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-06DOI: 10.1108/ijlss-12-2021-0214
R. Clancy, K. Bruton, D. O’Sullivan, Aidan Cloonan
Purpose Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study is to provide a framework to guide quality practitioners with the implementation of digitalisation in their existing practices. Design/methodology/approach A review of literature assessed how quality management and digitalisation have been integrated. Findings from the literature review highlighted the success of the integration of Lean manufacturing with digitalisation. A comprehensive list of Lean Six Sigma tools were then reviewed in terms of their effectiveness and relevance for the hybrid digitisation approach to process improvement (HyDAPI) framework. Findings The implementation of the proposed HyDAPI framework in an industrial case study led to increased efficiency, reduction of waste, standardised work, mistake proofing and the ability to root cause non-conformance products. Research limitations/implications The activities and tools in the HyDAPI framework are not inclusive of all techniques from Lean Six Sigma. Practical implications The HyDAPI framework is a flexible guide for quality practitioners to digitalise key information from manufacturing processes. The framework allows organisations to select the appropriate tools as needed. This is required because of the varying and complex nature of organisation processes and the challenge of adapting to the continually evolving Industry 4.0. Originality/value This research proposes the HyDAPI framework as a flexible and adaptable approach for quality management practitioners to implement digitalisation. This was developed because of the gap in research regarding the lack of procedures guiding organisations in their digital transition to Industry 4.0.
{"title":"The HyDAPI framework: a versatile tool integrating Lean Six Sigma and digitalisation for improved quality management in Industry 4.0","authors":"R. Clancy, K. Bruton, D. O’Sullivan, Aidan Cloonan","doi":"10.1108/ijlss-12-2021-0214","DOIUrl":"https://doi.org/10.1108/ijlss-12-2021-0214","url":null,"abstract":"\u0000Purpose\u0000Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study is to provide a framework to guide quality practitioners with the implementation of digitalisation in their existing practices.\u0000\u0000\u0000Design/methodology/approach\u0000A review of literature assessed how quality management and digitalisation have been integrated. Findings from the literature review highlighted the success of the integration of Lean manufacturing with digitalisation. A comprehensive list of Lean Six Sigma tools were then reviewed in terms of their effectiveness and relevance for the hybrid digitisation approach to process improvement (HyDAPI) framework.\u0000\u0000\u0000Findings\u0000The implementation of the proposed HyDAPI framework in an industrial case study led to increased efficiency, reduction of waste, standardised work, mistake proofing and the ability to root cause non-conformance products.\u0000\u0000\u0000Research limitations/implications\u0000The activities and tools in the HyDAPI framework are not inclusive of all techniques from Lean Six Sigma.\u0000\u0000\u0000Practical implications\u0000The HyDAPI framework is a flexible guide for quality practitioners to digitalise key information from manufacturing processes. The framework allows organisations to select the appropriate tools as needed. This is required because of the varying and complex nature of organisation processes and the challenge of adapting to the continually evolving Industry 4.0.\u0000\u0000\u0000Originality/value\u0000This research proposes the HyDAPI framework as a flexible and adaptable approach for quality management practitioners to implement digitalisation. This was developed because of the gap in research regarding the lack of procedures guiding organisations in their digital transition to Industry 4.0.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48464475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-23DOI: 10.1108/ijlss-09-2021-0166
P. Hines, Christian Butterworth, Caroline Greenlee, Cheryl M. Jekiel, Darrin Taylor
Purpose The purpose of this paper is to extend the People Value Stream concept further by developing a view of what the world would look like through the eyes of a positive psychology employee-centred lens. The authors hope to provide a frame for further discussion, research and practical application in this area. Design/methodology/approach In this conceptual paper, the authors draw on their collective 120 plus years of experience with Lean and Human Resource Management through leading, teaching, researching and consulting in the area. Findings The People Value Stream concept is extended here by ideating how the “Voice of the Employee” could be used to enhance the existing knowledge of Lean. Relying on a range of cognitive psychological theories, particularly Self-Determination Theory, the authors show how it might be possible to develop a highly engaged workforce primarily by unlocking their intrinsic motivation through a “Self-Development and Growth Cycle”. This cycle is the people-improvement version of the seminal Deming process-improvement PDCA cycle. It can be applied within a job crafting “Personal Cockpit”. The authors also highlight a range of outputs and wider implications that create a pull for team leaders and senior management wishing to move to a real Servant Leader model. It will also help those developing and supporting people-related policies and procedures both within organisations and in trade unions. Originality/value This paper turns the existing literature about people within Lean upside down. To the best of the authors’ knowledge, for the first time in an academic paper, it discusses what would be the implications for the Lean world if the authors truly started understanding and deploying the explicit “Voice of the Employee” rather than just the established Lean “Voice of the Owner”-led Hoshin Kanri approach. The authors show how a lack of knowledge in these areas by the Lean community is limiting Lean’s engagement of people and its sustainability.
{"title":"Turning the lean world upside down","authors":"P. Hines, Christian Butterworth, Caroline Greenlee, Cheryl M. Jekiel, Darrin Taylor","doi":"10.1108/ijlss-09-2021-0166","DOIUrl":"https://doi.org/10.1108/ijlss-09-2021-0166","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to extend the People Value Stream concept further by developing a view of what the world would look like through the eyes of a positive psychology employee-centred lens. The authors hope to provide a frame for further discussion, research and practical application in this area.\u0000\u0000\u0000Design/methodology/approach\u0000In this conceptual paper, the authors draw on their collective 120 plus years of experience with Lean and Human Resource Management through leading, teaching, researching and consulting in the area.\u0000\u0000\u0000Findings\u0000The People Value Stream concept is extended here by ideating how the “Voice of the Employee” could be used to enhance the existing knowledge of Lean. Relying on a range of cognitive psychological theories, particularly Self-Determination Theory, the authors show how it might be possible to develop a highly engaged workforce primarily by unlocking their intrinsic motivation through a “Self-Development and Growth Cycle”. This cycle is the people-improvement version of the seminal Deming process-improvement PDCA cycle. It can be applied within a job crafting “Personal Cockpit”. The authors also highlight a range of outputs and wider implications that create a pull for team leaders and senior management wishing to move to a real Servant Leader model. It will also help those developing and supporting people-related policies and procedures both within organisations and in trade unions.\u0000\u0000\u0000Originality/value\u0000This paper turns the existing literature about people within Lean upside down. To the best of the authors’ knowledge, for the first time in an academic paper, it discusses what would be the implications for the Lean world if the authors truly started understanding and deploying the explicit “Voice of the Employee” rather than just the established Lean “Voice of the Owner”-led Hoshin Kanri approach. The authors show how a lack of knowledge in these areas by the Lean community is limiting Lean’s engagement of people and its sustainability.\u0000","PeriodicalId":48601,"journal":{"name":"International Journal of Lean Six Sigma","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48446406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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